A. Ulutaş, F. Balo, Katarina Mirković, Željko Stević, M. Mostafa
In the context of sustainable buildings, an ecological study of building and insulating materials is critical since it may assist affirm or shift the path of new technology development. Utilising sustainable material is a part of the sustainable improvement. For this reason, material fabrication is the primary process for the energy usage and release of intense environmental gaseous. The fabrication of the insulation and building materials, as in every fabrication process, comprises an energy consumption of crude materials in addition to the pollutants’ release. In buildings, insulation is a relevant technological resolution for cutting energy usage. This study aims to assess the primary energy consumption and the environmental effects of the fabrication of building and thermal isolation materials by using a new hybrid MCDM model. The proposed new hybrid MCDM model includes Fuzzy FUCOM, CCSD and CRADIS methods. While the subjective weights of the criteria were determined with the fuzzy FUCOM method, the objective weights of the criteria were determined with the CCSD method. Construction materials were listed with the CRADIS method. According to the fuzzy FUCOM method, the most important criterion was determined as the CR3 criterion, while the most important criterion according to the CCSD method was determined as the CR1 criterion. According to the combined weights, the most important criterion was determined as the CR3 criterion. According to the CRADIS method, the material with the best performance was determined as Cement Plaster. The methodology used in this study is a novel approach therefore it has not been used in any study before. In addition, since the CRADIS method is a newly developed MCDM method, the number of articles related to this method is low. Therefore, this research gap will be filled with this study.
{"title":"MCDM MODEL FOR CRITICAL SELECTION OF BUILDING AND INSULATION MATERIALS FOR OPTIMISING ENERGY USAGE AND ENVIRONMENTAL EFFECT IN PRODUCTION FOCUS","authors":"A. Ulutaş, F. Balo, Katarina Mirković, Željko Stević, M. Mostafa","doi":"10.3846/jcem.2023.19569","DOIUrl":"https://doi.org/10.3846/jcem.2023.19569","url":null,"abstract":"In the context of sustainable buildings, an ecological study of building and insulating materials is critical since it may assist affirm or shift the path of new technology development. Utilising sustainable material is a part of the sustainable improvement. For this reason, material fabrication is the primary process for the energy usage and release of intense environmental gaseous. The fabrication of the insulation and building materials, as in every fabrication process, comprises an energy consumption of crude materials in addition to the pollutants’ release. In buildings, insulation is a relevant technological resolution for cutting energy usage. This study aims to assess the primary energy consumption and the environmental effects of the fabrication of building and thermal isolation materials by using a new hybrid MCDM model. The proposed new hybrid MCDM model includes Fuzzy FUCOM, CCSD and CRADIS methods. While the subjective weights of the criteria were determined with the fuzzy FUCOM method, the objective weights of the criteria were determined with the CCSD method. Construction materials were listed with the CRADIS method. According to the fuzzy FUCOM method, the most important criterion was determined as the CR3 criterion, while the most important criterion according to the CCSD method was determined as the CR1 criterion. According to the combined weights, the most important criterion was determined as the CR3 criterion. According to the CRADIS method, the material with the best performance was determined as Cement Plaster. The methodology used in this study is a novel approach therefore it has not been used in any study before. In addition, since the CRADIS method is a newly developed MCDM method, the number of articles related to this method is low. Therefore, this research gap will be filled with this study.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43667012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Construction industry workers; are exposed to serious safety and health risks, hazardous work environments, and intense physical work. This situation causes fatal and non-fatal accidents, reduces productivity, and causes a loss of money and time. Construction safety management can use wearable sensors to improve safety performance. Since there are many types of sensors and not all sensors can be used in construction applications, it is necessary to identify suitable and reliable sensors. This requirement causes a sensor selection problem. The study aims to determine the priority order of physiological and kinematic sensors in preventing risks in the construction industry. Within the scope of this purpose, five criteria and seven alternatives were determined in line with the literature research and expert opinions. The criteria weights were calculated with the AHP method, and the alternatives were ranked with PROMETHEE and AHP. Providing a proactive approach to the use of sensors in the construction industry will provide safer working conditions, identify workers at risk, and help identify and predict potential health and safety risks. It will contribute to the literature on improving construction health and safety management.
{"title":"SELECTION OF WEARABLE SENSORS FOR HEALTH AND SAFETY USE IN THE CONSTRUCTION INDUSTRY","authors":"Güler Aksüt, Tamer Eren","doi":"10.3846/jcem.2023.19175","DOIUrl":"https://doi.org/10.3846/jcem.2023.19175","url":null,"abstract":"Construction industry workers; are exposed to serious safety and health risks, hazardous work environments, and intense physical work. This situation causes fatal and non-fatal accidents, reduces productivity, and causes a loss of money and time. Construction safety management can use wearable sensors to improve safety performance. Since there are many types of sensors and not all sensors can be used in construction applications, it is necessary to identify suitable and reliable sensors. This requirement causes a sensor selection problem. The study aims to determine the priority order of physiological and kinematic sensors in preventing risks in the construction industry. Within the scope of this purpose, five criteria and seven alternatives were determined in line with the literature research and expert opinions. The criteria weights were calculated with the AHP method, and the alternatives were ranked with PROMETHEE and AHP. Providing a proactive approach to the use of sensors in the construction industry will provide safer working conditions, identify workers at risk, and help identify and predict potential health and safety risks. It will contribute to the literature on improving construction health and safety management.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45247472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chencheng He, Xuan Liu, Jiahui Bi, Xiaohua Wang, Jiaxin Li
To promote consumers to buy green housing, the paper tries to find the effect of information on consumers’ green housing purchasing behavior. It classifies the contents and providers of information and explores their different influences. The results show that: 1) Consumers’ age and environmental protection attitude have a significant impact on their purchasing behavior, while consumers’ gender and monthly income have no significant impact; 2) Consumers are more affected by information relating to the economy and indoor air quality. The detailed order of influence is as follows: information on loan at concessionary rates > cost saving in usage phase > indoor air quality > waste classification > investment benefit > carbon emission reduction > thermal comfort > acoustic environment > greening rate > luminous environment; 3) Consumers with higher environmental awareness care more about the information on living environment and carbon emission. Whereas, those with low awareness of environmental protection are more affected by information on economic benefits. 4) Regarding different information providers, the consumers are mostly impacted by the government, while the information from developers could induce limited effects. It could guide the government and developers to provide appropriate information to promote GH purchasing behavior.
{"title":"THE INFLUENCE OF INFORMATION ON RESIDENTS’ GREEN HOUSING PURCHASING BEHAVIOR: DIFFERENT INFORMATION CONTENTS AND PROVIDERS","authors":"Chencheng He, Xuan Liu, Jiahui Bi, Xiaohua Wang, Jiaxin Li","doi":"10.3846/jcem.2023.19518","DOIUrl":"https://doi.org/10.3846/jcem.2023.19518","url":null,"abstract":"To promote consumers to buy green housing, the paper tries to find the effect of information on consumers’ green housing purchasing behavior. It classifies the contents and providers of information and explores their different influences. The results show that: 1) Consumers’ age and environmental protection attitude have a significant impact on their purchasing behavior, while consumers’ gender and monthly income have no significant impact; 2) Consumers are more affected by information relating to the economy and indoor air quality. The detailed order of influence is as follows: information on loan at concessionary rates > cost saving in usage phase > indoor air quality > waste classification > investment benefit > carbon emission reduction > thermal comfort > acoustic environment > greening rate > luminous environment; 3) Consumers with higher environmental awareness care more about the information on living environment and carbon emission. Whereas, those with low awareness of environmental protection are more affected by information on economic benefits. 4) Regarding different information providers, the consumers are mostly impacted by the government, while the information from developers could induce limited effects. It could guide the government and developers to provide appropriate information to promote GH purchasing behavior.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41914444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jian Zhang, Yuan Cao, Linyue Xia, Desen Zhang, Wensheng Xu, Yang Liu
Frost resistance in very cold areas is an important engineering issue for the durability of concrete, and the efficient and accurate prediction of the frost resistance of concrete is a crucial basis for determining reasonable design mix proportions. For a quick and accurate prediction of the frost resistance of concrete, a Bayesian optimization (BO)-random forest (RF) approach was used to establish a frost resistance prediction model that consists of three phases. A case study of a key national engineering project results show that (1) the RF can be used to effectively screen the factors that influence concrete frost resistance. (2) R2 of BO-RF for the training set and the test set are 0.967 and 0.959, respectively, which are better than those of the other algorithms. (3) Using the test data from the first section of the project for prediction, good results are obtained for the second section. The proposed BO-RF hybrid algorithm can accurately and quickly predict the frost resistance of concrete, and provide a reference basis for intelligent prediction of concrete durability.
{"title":"INTELLIGENT PREDICTION OF THE FROST RESISTANCE OF HIGH-PERFORMANCE CONCRETE: A MACHINE LEARNING METHOD","authors":"Jian Zhang, Yuan Cao, Linyue Xia, Desen Zhang, Wensheng Xu, Yang Liu","doi":"10.3846/jcem.2023.19226","DOIUrl":"https://doi.org/10.3846/jcem.2023.19226","url":null,"abstract":"Frost resistance in very cold areas is an important engineering issue for the durability of concrete, and the efficient and accurate prediction of the frost resistance of concrete is a crucial basis for determining reasonable design mix proportions. For a quick and accurate prediction of the frost resistance of concrete, a Bayesian optimization (BO)-random forest (RF) approach was used to establish a frost resistance prediction model that consists of three phases. A case study of a key national engineering project results show that (1) the RF can be used to effectively screen the factors that influence concrete frost resistance. (2) R2 of BO-RF for the training set and the test set are 0.967 and 0.959, respectively, which are better than those of the other algorithms. (3) Using the test data from the first section of the project for prediction, good results are obtained for the second section. The proposed BO-RF hybrid algorithm can accurately and quickly predict the frost resistance of concrete, and provide a reference basis for intelligent prediction of concrete durability.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44737297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The construction and management of large-scale projects have the characteristics of complexity, dynamic and offline, and how to evaluate it is a research problem accurately. This study addresses this question through multidisciplinary cross-applied research. The research analyses and optimizes the environmental impact of the construction stage of superlarge bridges by establishing a theoretical model system of environmental impact resilience. The analysis shows that industrialized construction can save 56.31% of materials compared with traditional construction but increase the consumption of machinery and personnel by 11.18%. Ultimately, environmental pollution can be significantly reduced. This study breaks through the difficulty of accurately evaluating discrete dynamic factors. It has realized the application of multidisciplinary research to solve management optimization and design problems in the elastic and dynamic changes of super-large bridges during construction. This research provides rich theoretical models and advanced analytics experience data for environmental resilience impacts and project resilience management models, laying a solid scientific foundation for dynamic control and sustainable development assessment of statically indeterminate structures in the future.
{"title":"CARBON IMPACT ASSESSMENT OF BRIDGE CONSTRUCTION BASED ON RESILIENCE THEORY","authors":"Zhiwu Zhou, Julián Alcalá, V. Yepes","doi":"10.3846/jcem.2023.19565","DOIUrl":"https://doi.org/10.3846/jcem.2023.19565","url":null,"abstract":"The construction and management of large-scale projects have the characteristics of complexity, dynamic and offline, and how to evaluate it is a research problem accurately. This study addresses this question through multidisciplinary cross-applied research. The research analyses and optimizes the environmental impact of the construction stage of superlarge bridges by establishing a theoretical model system of environmental impact resilience. The analysis shows that industrialized construction can save 56.31% of materials compared with traditional construction but increase the consumption of machinery and personnel by 11.18%. Ultimately, environmental pollution can be significantly reduced. This study breaks through the difficulty of accurately evaluating discrete dynamic factors. It has realized the application of multidisciplinary research to solve management optimization and design problems in the elastic and dynamic changes of super-large bridges during construction. This research provides rich theoretical models and advanced analytics experience data for environmental resilience impacts and project resilience management models, laying a solid scientific foundation for dynamic control and sustainable development assessment of statically indeterminate structures in the future.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45726505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhibin Hu, Guangdong Wu, Junwei Zheng, Xianbo Zhao, J. Zuo
Construction project complexity can be daunting, so both academics and practitioners have been looking for guidance. Previous studies have attempted to reconcile the inconsistencies and complexities in the relationships among project complexity, project success, and project management success. However, such research has failed to establish these clear relationships. Accordingly, the approach of systematic review and meta-analysis is applied in this study to investigate and compare how different project complexity affects project success and project management success by selecting 22 articles and 77 effect sizes. The results indicate that integrational complexity significantly positively affects project success, whereas it is not significantly negatively associated with project management success. Within a technical-organizational-environmental (TOE) framework, effects of organizational, environmental, and technical complexity on project success and project management success are also discussed here. A possible moderator (the national/regional income level) is tested and verified. The findings contribute to the system of knowledge on project complexity and provide guidelines for decision-makers to achieve a balance between project success and project management success in routine operation of construction projects.
{"title":"UNRAVELLING EFFECTS OF PROJECT COMPLEXITY ON PROJECT SUCCESS AND PROJECT MANAGEMENT SUCCESS: A META-ANALYTIC REVIEW","authors":"Zhibin Hu, Guangdong Wu, Junwei Zheng, Xianbo Zhao, J. Zuo","doi":"10.3846/jcem.2023.19553","DOIUrl":"https://doi.org/10.3846/jcem.2023.19553","url":null,"abstract":"Construction project complexity can be daunting, so both academics and practitioners have been looking for guidance. Previous studies have attempted to reconcile the inconsistencies and complexities in the relationships among project complexity, project success, and project management success. However, such research has failed to establish these clear relationships. Accordingly, the approach of systematic review and meta-analysis is applied in this study to investigate and compare how different project complexity affects project success and project management success by selecting 22 articles and 77 effect sizes. The results indicate that integrational complexity significantly positively affects project success, whereas it is not significantly negatively associated with project management success. Within a technical-organizational-environmental (TOE) framework, effects of organizational, environmental, and technical complexity on project success and project management success are also discussed here. A possible moderator (the national/regional income level) is tested and verified. The findings contribute to the system of knowledge on project complexity and provide guidelines for decision-makers to achieve a balance between project success and project management success in routine operation of construction projects.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43632182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper evaluated the influence of Standard Penetration Test (SPT) correction factors, namely the hammer energy efficiency, borehole diameter, drill rod length, and sampling method, on the correlations between SPT resistance (SPT-N) and undrained shear strength (Su). Comparisons were made between new equations (with and without SPT corrections), which were derived from soil data collected from Penang Island, Malaysia. The coefficient of determination, Absolute Average Relative Error, Standard Deviation, and Analysis of Variance (ANOVA) were employed as the basis for the assessments. Finally, a comprehensive analysis was carried out to evaluate the relationship between uncorrected ratio (Su/N) or corrected ratio (Su/N60) and Plasticity Index (PI)/Liquidity Index (LI). Based on the results, all correction factors recorded a significant impact on the estimated Su, as the ANOVA calculation suggested that the borehole diameter correction was the most statistically significant. Furthermore, the Su/N and Su/N60 exhibited increasing trends with increased PI and LI, which may be attributed to the soil’s state and behaviour. Additionally, cubic regression is the best-fit equation to correlate the parameters. In summary, this study provided new insights into the influence of correction factors, which can be used to improve the accuracy of the empirical correlations and engineering designs.
{"title":"EFFECT OF STANDARD PENETRATION TEST CORRECTIONS ON THE ESTIMATION OF UNDRAINED SHEAR STRENGTH","authors":"Jia Jun Tan, H. Ramli","doi":"10.3846/jcem.2023.18441","DOIUrl":"https://doi.org/10.3846/jcem.2023.18441","url":null,"abstract":"This paper evaluated the influence of Standard Penetration Test (SPT) correction factors, namely the hammer energy efficiency, borehole diameter, drill rod length, and sampling method, on the correlations between SPT resistance (SPT-N) and undrained shear strength (Su). Comparisons were made between new equations (with and without SPT corrections), which were derived from soil data collected from Penang Island, Malaysia. The coefficient of determination, Absolute Average Relative Error, Standard Deviation, and Analysis of Variance (ANOVA) were employed as the basis for the assessments. Finally, a comprehensive analysis was carried out to evaluate the relationship between uncorrected ratio (Su/N) or corrected ratio (Su/N60) and Plasticity Index (PI)/Liquidity Index (LI). Based on the results, all correction factors recorded a significant impact on the estimated Su, as the ANOVA calculation suggested that the borehole diameter correction was the most statistically significant. Furthermore, the Su/N and Su/N60 exhibited increasing trends with increased PI and LI, which may be attributed to the soil’s state and behaviour. Additionally, cubic regression is the best-fit equation to correlate the parameters. In summary, this study provided new insights into the influence of correction factors, which can be used to improve the accuracy of the empirical correlations and engineering designs.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47224997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahboobeh Golestanizadeh, H. Sarvari, Daniel W. M. Chan, Nerija Banaitienė, A. Banaitis
In construction projects, managers make multiple decisions every day. Most of these decisions are relatively unimportant; some of them are critical and could lead to the success or failure of a construction project. To ensure construction companies make effective managerial decisions, decision making requires performing an initial technical and economic analysis, comparing different decision-making solutions, using a planning system, and ensuring project implementation based on the provided plans. Therefore, the use of powerful systems such as business intelligence (BI), which play a central role in management and decision-making, is essential in project-based companies. The current study aims to determine and evaluate the main managerial opportunities in the application of BI in project-based construction companies using a descriptive survey approach. An empirical research questionnaire consisting of 60 factors and 7 categories was adopted. The questionnaire, after confirming its validity and reliability, was distributed to 100 experts engaged in 5 active project-based construction companies who were familiar with BI topics. To analyse the data, a one-sample t-test and the Friedman test were performed using the SPSS software. The findings indicated that the importance of the identified opportunities for the use of BI in project-based construction companies is above average and that, in the case of using BI in such companies, these opportunities can be used to improve project performance. The results of the current study can help managers and other stakeholders as an effective decision-making tool to better implement BI in project-based companies.
{"title":"MANAGERIAL OPPORTUNITIES IN APPLICATION OF BUSINESS INTELLIGENCE IN CONSTRUCTION COMPANIES","authors":"Mahboobeh Golestanizadeh, H. Sarvari, Daniel W. M. Chan, Nerija Banaitienė, A. Banaitis","doi":"10.3846/jcem.2023.19533","DOIUrl":"https://doi.org/10.3846/jcem.2023.19533","url":null,"abstract":"In construction projects, managers make multiple decisions every day. Most of these decisions are relatively unimportant; some of them are critical and could lead to the success or failure of a construction project. To ensure construction companies make effective managerial decisions, decision making requires performing an initial technical and economic analysis, comparing different decision-making solutions, using a planning system, and ensuring project implementation based on the provided plans. Therefore, the use of powerful systems such as business intelligence (BI), which play a central role in management and decision-making, is essential in project-based companies. The current study aims to determine and evaluate the main managerial opportunities in the application of BI in project-based construction companies using a descriptive survey approach. An empirical research questionnaire consisting of 60 factors and 7 categories was adopted. The questionnaire, after confirming its validity and reliability, was distributed to 100 experts engaged in 5 active project-based construction companies who were familiar with BI topics. To analyse the data, a one-sample t-test and the Friedman test were performed using the SPSS software. The findings indicated that the importance of the identified opportunities for the use of BI in project-based construction companies is above average and that, in the case of using BI in such companies, these opportunities can be used to improve project performance. The results of the current study can help managers and other stakeholders as an effective decision-making tool to better implement BI in project-based companies.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49000175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dominic Page, L. Hou, P. Rahnamayiezekavat, M. F. Antwi-Afari, SangHyeok Han, Sungkon Moon
This paper presents the measured effects of different resource qualities on construction performance. The paper describes a recommended method, proposed with the concept of prediction by understanding the causal effect of process resources on consequent work efficiencies. The project team measured and compared the different arrangements of resources and their effects on on-site work efficiencies. The paper includes a field study of 15 operations (40 piles) in Melbourne, on several worksites of prefabricated piles and installations. It aimed to determine the causality between the set of delivered prefabricated piles and relevant work efficiencies. This field includes its purpose of generating and providing scientific evidence in effectively implementing an offsite operation. One of the critical factors affecting the efficiency of the installation process was confirmed to be the location of the longest section in the sequence. It took 21.8 minutes longer with the middle part of the installation if the longest section was designed to be in the middle of the whole prefabricated steel pile. The findings confirmed the need for holistic communication along the supply chain. The originality of this project is to provide a case study that offers archival evidence of the proposed model in a practical situation.
{"title":"EXPLORING EFFECT OF DIFFERENT RESOURCE QUALITIES ON PROCESS EFFICIENCY IN CONSTRUCTION PILE INSTALLATION","authors":"Dominic Page, L. Hou, P. Rahnamayiezekavat, M. F. Antwi-Afari, SangHyeok Han, Sungkon Moon","doi":"10.3846/jcem.2023.19215","DOIUrl":"https://doi.org/10.3846/jcem.2023.19215","url":null,"abstract":"This paper presents the measured effects of different resource qualities on construction performance. The paper describes a recommended method, proposed with the concept of prediction by understanding the causal effect of process resources on consequent work efficiencies. The project team measured and compared the different arrangements of resources and their effects on on-site work efficiencies. The paper includes a field study of 15 operations (40 piles) in Melbourne, on several worksites of prefabricated piles and installations. It aimed to determine the causality between the set of delivered prefabricated piles and relevant work efficiencies. This field includes its purpose of generating and providing scientific evidence in effectively implementing an offsite operation. One of the critical factors affecting the efficiency of the installation process was confirmed to be the location of the longest section in the sequence. It took 21.8 minutes longer with the middle part of the installation if the longest section was designed to be in the middle of the whole prefabricated steel pile. The findings confirmed the need for holistic communication along the supply chain. The originality of this project is to provide a case study that offers archival evidence of the proposed model in a practical situation.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49500804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wonseok Seo, Byungjoo Choi, Dongyoun Shin, Jinyoung Kim
The precast concrete (PC) method involves manufacturing reinforced concrete building components in a factory that are then transported to and assembled on a construction site. Compared to conventional methods, PC is widely employed as an advantageous means of creating a sustainable environment and improving construction quality. However, due to time and cost increase, many modern PC factories inspect only randomly selected component samples, for which they write inspection reports using paper-based forms. The storage and management of these documents associated with inspections within factories are essential because any defects that occur during the manufacturing process adversely affect the subsequent delivery and assembly activities. In this study, a mobile application capable of automated documentation and the storage, and input of systematic data was developed to generate a system for comprehensive quality management and assurance within PC factories. The developed system was tested in a PC factory, achieving a 47% time-saving rate compared to the conventional inspection method. Inspection reports of the developed system contain considerably more information than those of the conventional method and fundamentally prevent the risk of document damage and loss as they are automatically archived on a server in digital format.
{"title":"DEVELOPMENT OF A QUALITY MANAGEMENT SYSTEM FOR PRECAST CONCRETE FACTORIES","authors":"Wonseok Seo, Byungjoo Choi, Dongyoun Shin, Jinyoung Kim","doi":"10.3846/jcem.2023.19228","DOIUrl":"https://doi.org/10.3846/jcem.2023.19228","url":null,"abstract":"The precast concrete (PC) method involves manufacturing reinforced concrete building components in a factory that are then transported to and assembled on a construction site. Compared to conventional methods, PC is widely employed as an advantageous means of creating a sustainable environment and improving construction quality. However, due to time and cost increase, many modern PC factories inspect only randomly selected component samples, for which they write inspection reports using paper-based forms. The storage and management of these documents associated with inspections within factories are essential because any defects that occur during the manufacturing process adversely affect the subsequent delivery and assembly activities. In this study, a mobile application capable of automated documentation and the storage, and input of systematic data was developed to generate a system for comprehensive quality management and assurance within PC factories. The developed system was tested in a PC factory, achieving a 47% time-saving rate compared to the conventional inspection method. Inspection reports of the developed system contain considerably more information than those of the conventional method and fundamentally prevent the risk of document damage and loss as they are automatically archived on a server in digital format.","PeriodicalId":15524,"journal":{"name":"Journal of Civil Engineering and Management","volume":" ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46710622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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